Information and material for the course Generative AI at The Arctic University of Norway
The new version of the course is coming! The next edition will be in spring 2026.
The course will be streamed online. You can attend online or physically at the Tromsø (main place) and Bodø campuses.
Course code at UiT:
- Master students: INF-3600 and webpage
- PhD students: INF-8810 (same course but with an additional exam)
The course covers Large Language Models (LLMs), Generative AI for images as well as applied aspects such as continuous integration in production systems. The goal of the course is to provide a master-level introduction to Generative AI, combined with hands-on experience about these new technologies. The students will practice current state-of-the-art open-source tools for generative AI. At the end of the course the students will understand the concepts behind generative AI and be able to program and interact with their own generative models. The course is for students passionate about AI and generative AI. Some emphasis will be put on creating AI tools, which could lead to possible startup ideas. Programming skills in Python are required. Familiarity with machine learning terminology is expected. Knowledge of deep learning is not mandatory but recommended.
You will learn about
- the transformer achitecture and Large Language Models, how they work and how to run them (small versions) locally on your computer, how to parameter them,
- LLMs and their limits, are they stochastic parrots? Ethics in AI,
- fine-tuning AI models with LoRa,
- how you can combine LLMs with other tools for retrieving information in documents or making a recommender system, with RAG "Retrieval Augmented Generation" and Agentic AI,
- Multimodal LLMs with text and images,
- Generative AI for images and diffusion models, the principles and the practice with Huggingface and tools such as comfy.ui,
- chain-of-thoughts, LLM reasoning,
- and more!
You can find more information by looking at the last editions 2024 and 2025 in their respective folders.
You will be evaluated on a team project you develop over the semester. This project will be a software or demo making use of the tools and concepts we see in class (see folder of the previous years for some examples). PhD students will have an additional task of presenting a scientific paper during one of the lectures.
You can register if you are:
- a master student at UiT
- a PhD student at any university in Norway
- Master students: register on studentweb.
- PhD students: course code INF-8810, registration before 6th of December, contact the course leaders
Course leaders:
- Helge Fredriksen (Bodø campus), helge.fredriksen@uit.no
- Benjamin Ricaud (Tromsø campus), benjamin.ricaud@uit.no
You can find information about previous years in the dedicated folders
This UiT course is supported by the center of excellence SFF Integreat.
